How Small Businesses Can Use Artificial Intelligence to Outrun the Competition

Small businesses cannot afford to wait or ignore artificial intelligence and leave it to big companies and universities. Here are cost effective strategies to save money, build experience and gain advantages over the competition.

When you hear artificial intelligence (AI), you may think of things like "The Terminator," top research universities or huge tech companies like Google, Amazon and Microsoft. For small businesses, the topic may seem too complicated and or too expensive to deal with, and the natural reaction may be to ignore it and go back to work.

But you can't afford to ignore AI. AI can move faster and be more transformative than other technologies. Computers and the internet allowed for innovative and faster ways of doing things, which disrupted a lot of businesses and jobs. This year venture capital firms have already invested $3.6B in AI startups. Big companies including Amazon, Apple, Google, Microsoft and many more are investing many billions more. Small businesses can start using AI to their advantage by leveraging the products all those companies are releasing.

What does AI really entail?

Artificial intelligence has become an umbrella term for several technologies. However, it is not really the proper use of the term. “AI” should refer to software that mimics independent thought and it is still mainly found in research labs. Instead, look at these related technologies:

Machine Learning: Machine learning is what people often mean when they talk about AI applications. Machine learning is software that isn’t limited by the specific computer instructions its programmer wrote. It is more flexible and requires less programming than traditional software. Machine learning changes the way software behaves based on data or results.

Smart Robots: Smart robots add machine learning and other technologies to automate tasks and reduce labor. For example, "Flippy" is a robot that makes fast food hamburgers. It builds on decades of successful applications of robotics in manufacturing. Amazon has more than 45,000 robots working in its fulfillment centers.

Virtual Assistants: VAs are getting much more sophisticated and will revolutionize service and sales functions. On websites, these are starting to complete transactions for customers and will replace menus and forms. Amy from X.ai will schedule meetings for you. IBM’s Watson will walk someone through setting up a new bank account and it can set up a brokerage account for you. Capital One is using VAs to allow customers to easily transfer money or pay bills.

Speech recognition: This is a way for computer programs to listens to human speech and understand it. You are familiar with call center IVRs that frustrate you as you struggle to make it understand your pronunciation of whose limited menu options don’t quite fit your needs. The technology is improving quickly and machine learning is helping the speech recognition systems get much more accurate and successful at completing tasks.

Natural Language Generation: NLG analyzes data and then writes human-readable text from it. This will revolutionize business intelligence and reporting. NarrativeWave consumes raw data from industrial applications and then generates insights or optimizes processes. Environment Canada uses NLG to automatically write weather reports in both French and English. Forbes uses NLG to summarize and explain company earnings reports.

Decision Management: The terms “Enterprise Decision Management” and “Business Decision Management” are both used to describe automated decision making. Often, they combine with one or more of the other technologies described to analyze information and partially or totally automate decision making.

What can your business do to take advantage of AI?

Start familiarizing yourself with these technologies. You can do this right from the comfort of your own home. Amazon Echo and Google Home are great consumer touchpoints to AI and a good example of voice to text and data technologies.

Rethink your business. Start with a blank whiteboard and ask yourself where in your industry you could develop a competitive advantage by solving new problems or automating tasks. Express these in business terms with measurable goals and then get some expert advice on how to implement them.

Start small and reinvest cost savings into more potentially transformative applications. If your website deals with a lot of inquiries or you take a lot of customer telephone calls then add a chatbot and start researching products that utilize voice recognition. Chatbots have reduced support costs by as much as 30 percent.

Don’t feel bad about job destruction. It is the tip of an iceberg and you cannot afford to stand by as competitors reduce costs through automation and optimize process utilizing data analytics, machine learning and decision management. These technologies can allow competition to come from very unexpected places. Amazon demonstrated this when it went from an ecommerce company to competing against Google and Microsoft. Now it is demonstrating it in meal delivery and grocery services.

Get really data driven. Really think about the KPIs that make your business work and optimize around them one at a time. Every successful AI strategy starts with a foundation of good data. Slice data and stay away from averages. Averages hide opportunity. Put the time into cohort analysis and find the slices of your critical processes that deliver the most value. Scale those up and think about how optimization and automation could take that to the next level. Be proactive and make technology a central part of your strategy.

Most of your access to AI will be from vendor products. Track who is investing in technology that you could use. Invest in solutions from companies who are investing big in data and automation. They will build AI into their products and you will get massive competitive advantage from them.

Make leaps ahead. Don’t fear some failures along the way. Revolutionize one part of your business. Think how you could outpace everyone in your industry in one critical business process. Just make sure its impact on the business relates to a major shift in quality, service or cost. You don’t have to outrun the technology companies, but you do need to outrun your competition.

Microsoft alum with internet & software focus. My main technical interests are the application of AI, machine learning, analytics and big data. I have several ongoing projects in those areas. Completed.com applies machine learning to large data sets to measure, rate, score and track human professional review activities. Our goal is to improve rating platforms and to leverage user generated content while applying technology to make it safer, more reliable, more relevant and better quality.
Cloud Commerce Consulting provides advisory services. We focus on technology strategies (especially analytics, big data and machine learning) and scale strategies for growth companies (including sales and marketing and operational transformations). In addition to machine learning we are interested in broader artificial intelligence applications.
I also worked at Microsoft as a manager at the Redmond headquarters. My team worked across business units on product development projects for identity (Active Directory), communications and integration (BizTalk, Host Integration, RFID, Windows Communications), workflow (Windows Workflow and some early workflow modeling projects), commerce (Microsoft Commerce Server) and I was involved in the early business strategy efforts related to modeling language projects that led to Oslo and the 'M' language.
My background includes analytics platforms (Chaikin Analytics and Brand.com), big data information and search technologies (Completed.com, Brand.com and ChaCha Search) and SaaS commerce and business platforms often with an emphasis on predictive analytics (Ontario Systems, Ecometry, Sapago).

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